AI-Powered Migration Platform

Migrate Any Database
to the Cloud —
Without the Risk

AI agents automate schema mapping, validation, and live cutover for any source-to-target database pair. Zero downtime. Zero errors. Enterprise-grade.

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100+
Migrations
Completed
99.97%
Uptime
SLA
20+
Database
Types
🔒 platform.dflux.ai
LIVE
Dflux.ai migration dashboard showing MySQL to Snowflake migration completed in 1m 28s — enterprise database migration platform
MySQL → Snowflake
✓ Completed in 1m 28s
9 AI Agents
Trusted by engineering teams at
Procter & Gamble
Larsen & Toubro
Cyient
DRDO
Mouri Tech
Flexivan
The Problem

Database Migration
is Broken

Manual processes waste months of engineering time and create dangerous production windows.
⏳
Months of Manual Work
Schema analysis, mapping, and testing consume entire quarters of engineering bandwidth — pulling your best engineers off product development.
⚡
Dangerous Downtime Risk
Traditional migrations require maintenance windows that impact customers, violate SLAs, and create cascading failures across dependent services.
💸
Costly Data Errors
Manual scripts introduce type mismatches, truncations, and data loss at scale — errors that can take months to detect and remediate.
The Solution

AI That Handles
the Entire Migration

Dflux.ai deploys specialised AI agents that analyse your source database, generate schema mappings, execute live migrations, and validate every row — automatically.
See How It Works
01
Analyze
AI scans your source schema, indexes, constraints, and data volumes. Identifies migration complexity and risk areas.
Schema Analysis Agent
02
Map
Automatically generates target schema mappings, resolves type conflicts, and flags breaking changes for review.
Data Mapping Agent
03
Migrate
Live migration with dual-write sync. Source and target stay aligned throughout. Cutover happens in seconds, not hours.
Migration Execution Agent
04
Validate
Post-migration row count checks, checksums, and statistical anomaly detection. Automated rollback if thresholds breach.
Validation Agent
Platform Features

Built for Enterprise-Scale Migration

Every feature you need to migrate the most complex databases safely, quickly, and without disruption.
🤖
AI Schema Mapping
Automatically detects data types, constraints, and relationships. Resolves cross-database type conflicts with AI-generated suggestions.
⚡
Zero-Downtime Migration
Dual-write synchronisation keeps source and target aligned throughout. Controlled cutover with instant rollback capability.
🗃️
20+ Database Types
PostgreSQL, MySQL, Oracle, SQL Server, MongoDB, Cassandra, Redis, DynamoDB, Snowflake, BigQuery, Redshift, and more.
✅
Automated Validation
Row count verification, checksum validation, and statistical anomaly detection. Generates a full integrity report post-migration.
🔒
Enterprise Security
AES-256 encryption at rest and in transit. Role-based access control, SOC2 Type II compliance, and a complete audit trail.
📊
Live Monitoring
Real-time throughput dashboards, configurable alerts, and detailed migration logs. Full observability throughout every stage.
500+
Migrations Completed
99.97%
Uptime SLA
70%
Faster Than Manual
20+
Database Types
How It Works

From Connect to Complete
in Four Steps

Step 01
🔌
Connect Source
Connect your source database using secure credentials. Dflux supports direct connection, VPN, and private link.
→
Step 02
🧠
AI Analyses Schema
Our AI scans your entire schema and auto-generates optimised target mappings in minutes — not weeks.
→
Step 03
🚀
Live Migration
Migration runs live against production. Dual-write keeps everything in sync until you're ready to cut over.
→
Step 04
🎯
Validate & Done
Automated integrity checks confirm everything is correct. One-click cutover. Rollback available at any point.
Customer Stories

Trusted by Data Teams
at Scale

“
We migrated 11 years of production Oracle data to PostgreSQL in a single weekend. What our team estimated at 14 weeks took 4 days. The schema mapping alone would have taken us a month manually.
JH
James Hartwell
VP of Engineering, Fintech SaaS — London, UK
“
The auto-rollback triggered once when it detected a row count mismatch. It reverted cleanly in 8 minutes. That safety net alone justified the entire cost. Our previous attempt took three weeks to clean up.
SR
Sarah Renwick
Head of Data Engineering, Healthcare Platform — Manchester, UK
“
We evaluated five tools. Dflux was the only one with actual AI-driven schema analysis, not just an ETL wrapper. The observability dashboard during migration is genuinely impressive — you see exactly what every agent is doing.
MP
Marcus Peterson
CTO, E-commerce Infrastructure — Austin, TX, USA
Get Started Today
Ready to Modernise
Your Data Infrastructure?
Join 100+ data teams who have already migrated to the cloud with zero downtime and full confidence.
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